speechbrain/speechbrain

Health v2 · maintenance only

Adoption not part of the score

11785 stars · 1718 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

SpeechBrain is an open-source PyTorch-based speech toolkit for building conversational AI systems. It provides training recipes, pretrained models, and tools for speech recognition, speaker recognition, speech enhancement/separation, TTS, and language modeling.

Use cases

• transcribe speech to text with pretrained models
• fine-tune whisper or wav2vec2 on my own dataset
• verify speaker identity from voice recordings
• separate overlapping speakers in an audio file
• enhance noisy speech recordings
• train a speech recognition model from scratch
• build a voice assistant pipeline
• diarize who spoke when in a meeting recording

When to choose

• you want a flexible PyTorch-based toolkit covering many speech tasks with 200+ training recipes
• you need to fine-tune HuggingFace pretrained speech models like Whisper, Wav2Vec2, or WavLM
• you are doing speech research and want customizable, well-documented training pipelines

When to avoid

• you only need a quick off-the-shelf transcription API with no training or customization
• your project is not Python/PyTorch based
• you need production-grade low-latency streaming ASR out of the box without building it yourself

Facets

library · maturity active

speech-recognition audio-processing machine-learning deep-learning tts nlp llm-training speech-processing machine-learning deep-learning artificial-intelligence python cross-platform pytorch conversational-ai asr speaker-recognition speech-enhancement speech-separation huggingface training-recipes diarization natural-language-processing audio gpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="speechbrain/speechbrain")